Please use this identifier to cite or link to this item:
|Scopus||Web of Science®||Altmetric|
|Title:||Automated quantification of lung structures from optical coherence tomography images|
|Citation:||Biomedical Optics Express, 2013; 4(11):2383-2395|
|Publisher:||Optical Society of America|
|Alex M. Pagnozzi, Rodney W. Kirk, Brendan F. Kennedy, David D. Sampson, and Robert A. McLaughlin|
|Abstract:||Characterization of the size of lung structures can aid in the assessment of a range of respiratory diseases. In this paper, we present a fully automated segmentation and quantification algorithm for the delineation of large numbers of lung structures in optical coherence tomography images, and the characterization of their size using the stereological measure of median chord length. We demonstrate this algorithm on scans acquired with OCT needle probes in fresh, ex vivo tissues from two healthy animal models: pig and rat. Automatically computed estimates of lung structure size were validated against manual measures. In addition, we present 3D visualizations of the lung structures using the segmentation calculated for each data set. This method has the potential to provide an in vivo indicator of structural remodeling caused by a range of respiratory diseases, including chronic obstructive pulmonary disease and pulmonary fibrosis.|
|Keywords:||(100.0100) Image processing|
(100.2960) Image analysis
(110.4500) Optical coherence tomography
|Rights:||© 2013 Optical Society of America|
|Appears in Collections:||Aurora harvest 8|
Files in This Item:
There are no files associated with this item.
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.